python3 -m verl.trainer.main_ppo \
data.train_files=$DATA_DIR/train.parquet \
data.val_files=$DATA_DIR/test.parquet \
data.train_batch_size=4 \
data.val_batch_size=4 \
data.max_prompt_length=512 \
data.max_response_length=2048 \
actor_rollout_ref.model.path=$BASE_MODEL \
actor_rollout_ref.actor.optim.lr=1e-6 \
actor_rollout_ref.model.use_remove_padding=True \
actor_rollout_ref.actor.ppo_mini_batch_size=4 \
actor_rollout_ref.actor.ppo_micro_batch_size=4 \
actor_rollout_ref.actor.fsdp_config.param_offload=False \
actor_rollout_ref.actor.fsdp_config.grad_offload=False \
actor_rollout_ref.actor.fsdp_config.optimizer_offload=False \
actor_rollout_ref.rollout.temperature=0.6 \
actor_rollout_ref.rollout.top_k=1 \
actor_rollout_ref.rollout.do_sample=True \
actor_rollout_ref.rollout.n=2 \
actor_rollout_ref.rollout.log_prob_micro_batch_size=4 \
actor_rollout_ref.rollout.tensor_model_parallel_size=1 \
actor_rollout_ref.rollout.gpu_memory_utilization=0.2 \
actor_rollout_ref.ref.log_prob_micro_batch_size=4 \
actor_rollout_ref.ref.fsdp_config.param_offload=True \
critic.optim.lr=1e-5 \
critic.model.use_remove_padding=True \
critic.model.path=$BASE_MODEL \
critic.ppo_micro_batch_size=4 \
critic.model.fsdp_config.param_offload=False \
critic.model.fsdp_config.grad_offload=False \
critic.model.fsdp_config.optimizer_offload=False \
algorithm.kl_ctrl.kl_coef=0.001 \
trainer.logger=['wandb'] \
+trainer.val_before_train=False \
trainer.default_hdfs_dir=null \
trainer.n_gpus_per_node=$N_GPUS \
trainer.nnodes=1 \
trainer.save_freq=100 \
trainer.test_freq=20 \
trainer.project_name=KK_logic \
trainer.experiment_name=$EXPERIMENT_NAME \
trainer.total_epochs=1 2>&1 | tee verl_demo.log